Stochastic Processes

Marginal Tail-Adaptive Normalizing Flows ICML 2022 Markov Chain Monte Carlo for Continuous-Time Switching Dynamical Systems ICML 2022 Maximum Consensus by Weighted Influences of Monotone Boolean Functions CVPR 2022 Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling JMLR 2022 More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize ICML 2022 Multi-fidelity Monte Carlo: a pseudo-marginal approach NeurIPS 2022 Multiple Testing in Nonparametric Hidden Markov Models: An Empirical Bayes Approach JMLR 2022 On the Theoretical Properties of Noise Correlation in Stochastic Optimization NeurIPS 2022 Orbital MCMC AISTATS 2022 Perfect Sampling from Pairwise Comparisons NeurIPS 2022 Phase transitions in when feedback is useful NeurIPS 2022 Power-Law Escape Rate of SGD ICML 2022 Probabilistic Numerical Method of Lines for Time-Dependent Partial Differential Equations AISTATS 2022 Random Graph Matching in Geometric Models: the Case of Complete Graphs COLT 2022 Re-Analyze Gauss: Bounds for Private Matrix Approximation via Dyson Brownian Motion NeurIPS 2022 Reconstruction on Trees and Low-Degree Polynomials NeurIPS 2022 Rejection sampling from shape-constrained distributions in sublinear time AISTATS 2022 Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning ICML 2022 Sampling from Arbitrary Functions via PSD Models AISTATS 2022 Sampling from Log-Concave Distributions with Infinity-Distance Guarantees NeurIPS 2022 Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes ICML 2022 Segmenting Numerical Substitution Ciphers EMNLP 2022 Signature Moments to Characterize Laws of Stochastic Processes JMLR 2022 Sqrt(d) Dimension Dependence of Langevin Monte Carlo ICLR 2022 Three rates of convergence or separation via U-statistics in a dependent framework JMLR 2022